Samsung Galaxy Z Fold4
Geekbench ML Score
479
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 25 2024 10:51 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy Z Fold4 |
| Model ID | samsung SM-F936B |
| Motherboard | taro |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 2 part 3400 revision 0 |
| Base Frequency | 2.02 GHz |
| Cluster 1 | 4 Cores @ 2.02 GHz |
| Cluster 2 | 3 Cores @ 2.75 GHz |
| Cluster 3 | 1 Core @ 3.19 GHz |
| Memory Information | |
|---|---|
| Size | 11.00 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
210
39.2 IPS |
|
|
Image Classification (F16)
|
100% |
209
39.2 IPS |
|
|
Image Classification (I8)
|
97% |
581
108.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
263
4.40 IPS |
|
|
Image Segmentation (F16)
|
100% |
262
4.38 IPS |
|
|
Image Segmentation (I8)
|
98% |
615
10.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
345
0.42 IPS |
|
|
Pose Estimation (F16)
|
100% |
339
0.41 IPS |
|
|
Pose Estimation (I8)
|
100% |
1455
1.76 IPS |
|
|
Object Detection (F32)
|
100% |
217
16.2 IPS |
|
|
Object Detection (F16)
|
100% |
216
16.1 IPS |
|
|
Object Detection (I8)
|
61% |
637
47.6 IPS |
|
|
Face Detection (F32)
|
100% |
567
6.74 IPS |
|
|
Face Detection (F16)
|
100% |
560
6.66 IPS |
|
|
Face Detection (I8)
|
86% |
1396
16.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
466
3.61 IPS |
|
|
Depth Estimation (F16)
|
100% |
466
3.62 IPS |
|
|
Depth Estimation (I8)
|
95% |
1409
10.9 IPS |
|
|
Style Transfer (F32)
|
100% |
764
1.00 IPS |
|
|
Style Transfer (F16)
|
100% |
756
0.99 IPS |
|
|
Style Transfer (I8)
|
98% |
2044
2.69 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
227
8.10 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
230
8.22 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
895
31.9 IPS |
|
|
Text Classification (F32)
|
100% |
287
412.1 IPS |
|
|
Text Classification (F16)
|
100% |
287
412.4 IPS |
|
|
Text Classification (I8)
|
92% |
520
746.8 IPS |
|
|
Machine Translation (F32)
|
100% |
494
9.09 IPS |
|
|
Machine Translation (F16)
|
100% |
490
9.02 IPS |
|
|
Machine Translation (I8)
|
64% |
635
11.7 IPS |
